Correlation Between Mfs Emerging and Baird Intermediate
Can any of the company-specific risk be diversified away by investing in both Mfs Emerging and Baird Intermediate at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Mfs Emerging and Baird Intermediate into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mfs Emerging Markets and Baird Intermediate Bond, you can compare the effects of market volatilities on Mfs Emerging and Baird Intermediate and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Mfs Emerging with a short position of Baird Intermediate. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mfs Emerging and Baird Intermediate.
Diversification Opportunities for Mfs Emerging and Baird Intermediate
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Mfs and Baird is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding Mfs Emerging Markets and Baird Intermediate Bond in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Baird Intermediate Bond and Mfs Emerging is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Mfs Emerging Markets are associated (or correlated) with Baird Intermediate. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Baird Intermediate Bond has no effect on the direction of Mfs Emerging i.e., Mfs Emerging and Baird Intermediate go up and down completely randomly.
Pair Corralation between Mfs Emerging and Baird Intermediate
Assuming the 90 days horizon Mfs Emerging Markets is expected to generate 1.31 times more return on investment than Baird Intermediate. However, Mfs Emerging is 1.31 times more volatile than Baird Intermediate Bond. It trades about 0.04 of its potential returns per unit of risk. Baird Intermediate Bond is currently generating about -0.03 per unit of risk. If you would invest 1,204 in Mfs Emerging Markets on September 2, 2024 and sell it today you would earn a total of 8.00 from holding Mfs Emerging Markets or generate 0.66% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Mfs Emerging Markets vs. Baird Intermediate Bond
Performance |
Timeline |
Mfs Emerging Markets |
Baird Intermediate Bond |
Mfs Emerging and Baird Intermediate Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mfs Emerging and Baird Intermediate
The main advantage of trading using opposite Mfs Emerging and Baird Intermediate positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mfs Emerging position performs unexpectedly, Baird Intermediate can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Baird Intermediate will offset losses from the drop in Baird Intermediate's long position.Mfs Emerging vs. Mfs Prudent Investor | Mfs Emerging vs. Mfs Prudent Investor | Mfs Emerging vs. Mfs Prudent Investor | Mfs Emerging vs. Mfs Prudent Investor |
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Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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